Search Results for "can"
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Showing 65 open source projects for "can"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Finance Database
This is a database of 300.000+ symbols containing Equities, ETFs, etc.
As a private investor, the sheer amount of information that can be found on the internet is rather daunting. Trying to understand what type of companies or ETFs are available is incredibly challenging with there being millions of companies and derivatives available on the market. Sure, the most traded companies and ETFs can quickly be found simply because they are known to the public (for example, Microsoft, Tesla, S&P500 ETF or an All-World ETF). -
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OpenBB Terminal
Investment research for everyone, anywhere
...This is ideal for finance content creation. Create notebook templates (through papermill) which can be run on different tickers. This level of automation allows to speed up the development of your investment thesis and reduce human error. -
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Qlib
Qlib is an AI-oriented quantitative investment platform
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib. With Qlib, users can easily try their ideas to create better Quant investment strategies. At the module level, Qlib is a platform that consists of above components. The components are designed as loose-coupled modules and each component could be used stand-alone. -
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Qbot
AI-powered Quantitative Investment Research Platform
...For evaluation and analysis, Qbot integrates reporting and visualization (tearsheets, metrics) so you can compare performance across runs and inspect trade-level behavior. It supports multiple strategy runtimes and backtesting engines, is organized for extensibility (strategies live in a dedicated folder). -
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
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Polar.sh
Polar is the best funding & monetization platform for developers
Focus on building your passion, while we focus on the infrastructure to get you paid. Your Polar page can be displayed as an official funding option across your GitHub repositories. Get one-time donations of support from your community with ease. Turn issues into a crowdfunded backlog and share the funding with your contributors. -
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QuantDinger
AI-driven, local-first quantitative trading platform for research
...Unlike cloud-locked quant services, it lets users run the entire trading workflow on their own infrastructure using Docker, with a PostgreSQL database backend, a Python backend API, and a web frontend UI that supports visualization and strategy management. Traders and researchers can develop custom strategies in Python, run historical backtests, analyze performance, and connect to supported exchanges for live trading, making it suitable for equities, crypto, forex, and futures markets in a local environment. QuantDinger also incorporates optional AI features via external APIs, assisting in tasks like strategy ideation or interpreting market indicators, but strategy logic remains inspectable and transparent in code. -
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AI Hedge Fund
An AI Hedge Fund Team
...The project underlines AI’s potential in investment strategies but also carries disclaimers that it is for research and not financial advice. The implementation is designed so developers can study the pipeline end-to-end: from data ingestion through modeling to simulated portfolio management. -
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Tally
Let agents classify your bank transactions
...At its core, Tally pairs a local rule engine with large language models so that an AI assistant (like Claude Code, Copilot, or any CLI agent) interprets, suggests, and categorizes expenses, savings, subscriptions, and income events based on your own rules and behavior. It generates human-readable reports and can produce HTML, JSON, or Markdown outputs to suit dashboards or personal finance workflows. The project emphasizes transparency, allowing users to see why a particular transaction was classified a certain way and to refine rules over time. While it’s tailored toward developers and advanced users, it also includes an interactive command-line experience for initializing budgets, generating charts, and diving deep into spending patterns. -
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Yahoo! Finance market data downloader
Yahoo! Finance market data downloader
Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop working. yfinance aims to solve this problem by offering a reliable, threaded, and Pythonic way to download historical market data from Yahoo! finance. yfinance aimed to offer a temporary fix to the problem by scraping the data from Yahoo! Finance and returning a the data in the same format as pandas_datareader's get_data_yahoo(), thus keeping the code changes in existing software to a... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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NautilusTrader
A high-performance algorithmic trading platform
NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the... -
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Prophet
Tool for producing high quality forecasts for time series data
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal... -
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WYGIWYH
A simple but powerful self-hosted finance tracker
...The app supports multiple currencies, customizable transaction types, and built-in tools like dollar-cost averaging tracking to help you see investment activity alongside regular expenses, making it flexible for real world financial situations and global use. Its interface is designed to prioritize clarity and ease of entry, so you can quickly record and review spending without being overwhelmed by features you don’t need. -
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PyBroker
Algorithmic Trading in Python with Machine Learning
...Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance. -
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VisiData
A terminal spreadsheet multitool for discovering and arranging data
VisiData is an interactive multitool for tabular data. It combines the clarity of a spreadsheet, the efficiency of the terminal, and the power of Python, into a lightweight utility that can handle millions of rows with ease. A terminal interface for exploring and arranging tabular data. VisiData supports tsv, CSV, SQLite, JSON, xlsx (Excel), hdf5, and many other formats. Requires Linux, OS/X, or Windows (with WSL). Hundreds of other commands and options are also available; see the documentation. Code in the stable branch of this repository, including the main vd application, loaders, and plugins, is available for use and redistribution under GPLv3. ... -
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Google Spreadsheets Python
Google Sheets Python API
...Older versions of gspread have used oauth2client. Google has deprecated it in favor of google-auth. If you’re still using oauth2client credentials, the library will convert these to google-auth for you, but you can change your code to use the new credentials to make sure nothing breaks in the future. If you familiar with the Jupyter Notebook, Google Colaboratory is probably the easiest way to get started using gspread. -
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
...Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. The framework also tends to include automation layers for deployment, enabling trained models to operate in live or simulated environments with scheduled re-training and risk controls in place. -
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ThetaGang
ThetaGang is an IBKR bot for collecting money
...For example, you might want to use a 60/40 portfolio with SPY (S&P500 fund) and TLT (20-year treasury fund). This strategy reduces risk, but may also limit gains from big market swings. By reducing risk, one can increase leverage. ThetaGang will try to acquire your desired allocation of each stock or ETF according to the weights you specify in the config. To acquire the positions, the script will write puts when conditions are met. -
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Optopsy
A nimble options backtesting library for Python
Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads the heavy work of backtesting option strategies, the API is designed to be simple and easy to implement into your regular Panda's data analysis workflow. As such, we just need to call the long_calls() function to have Optopsy generate all combinations of a simple long call strategy for the specified time period and return a DataFrame. ... -
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alpha_vantage
A python wrapper for Alpha Vantage API for financial data.
Alpha Vantage delivers a free API for real time financial data and most used finance indicators in a simple json or pandas format. This module implements a python interface to the free API provided by Alpha Vantage. You can have a look at all the API calls available in their API documentation. For code-less access to the APIs, you may also consider the official Google Sheet Add-on or the Microsoft Excel Add-on by Alpha Vantage. To get data from the API, simply import the library and call the object with your API key. Next, get ready for some awesome, free, realtime finance data. ... -
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NeuralProphet
A simple forecasting package
NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in doubt. ... -
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KherveSheet
Excel for scientists: high-quality plots, Python in cells, AI side bar
...You have full control over axes, scales, ticks, titles and grids. Curve fitting and peak fitting are supported, with goodness-of-fit reporting overlaid on the plot. Every cell can also run a full Python program, not just a formula. An integrated AI assistant can generate the cell code from a plain-language description if needed. Learn by doing with 300 ready-made scientific examples covering plotting, data analysis, fitting and simulation. Built entirely in Python, KherveSheet adds a familiar Excel-style grid, an optimisation solver, and a native .ksheet format with CSV and Excel import/export. ... -
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SnacTrac
The cash-based snack bar manager!
SnacTrac is a tool designed to simplify managing a cash-based snack bar. After creating an account with admin approval, customers can use SnacTrac as a self-service purchasing kiosk. The system automatically tracks customer tabs and inventory, maintains purchase history, and provides an admin control panel with configurable user debt limits and more! -
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Repoint POS from South Africa is built for the speed of modern retail. We’ve eliminated technical friction to create a high-performance system that your team can master in minutes. It’s powerful commerce, simplified.
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ManagerSheet
A one-page investment portfolio report
ManagerSheet is a one-page investment portfolio report, that analyses and presents an investment portfolio with respect to: - Performance - Investment style - Risk More information on the report concept and instructions on how to create one's own portfolio reports can be found at the ManagerSheet Web Site under the "Documentation" section. Please note that the project is in alpha stage. -
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Money Math
Smart financial calculator for savings, discounts and payments
Looking for a simple yet powerful financial tool? Our calculator app helps you easily manage your money with four key features. You can calculate how much your savings will grow with interest — just enter your deposit, rate, and period. It’s perfect for planning your investments. The app also helps you understand discounts — input the original price and discount percentage, and see the final price instantly. Managing regular payments is simple: just enter the amount, frequency, and duration to find out your total expenses. ...